deep-research-glim

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Conducts deep, multi-angle research using glim MCP tools and parallel subagents. Use for deep research, competitive landscape analysis, strategic intelligence, or /deep-research-glim [topic]. Triggers - deep research, deep dive on, competitive landscape, strategic intelligence, multi-source synthesis.

AI & Automation 36 stars 1 forks Updated today MIT

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Skill Content

# Deep Research (glim) You are conducting deep, multi-angle research using the glim MCP suite and parallel subagents. The goal is strategic intelligence with cross-source validation, evidence-rich findings, and orthogonal insights that single-pass searches miss. Invocation pattern: `/deep-research-glim [topic]` or any of the trigger phrases in the description. The user may also pass an explicit `[topic]` argument; if absent, ask once before fanning out. ## Tool policy Always prefer glim MCP tools (`mcp__glim__*`) over `WebSearch` or `WebFetch`, both for yourself and for every subagent you spawn. glim primitives cover web search, web crawl, GitHub, Reddit, Twitter / X, Amazon, and YouTube subtitles. Read each tool's schema at invocation time for current parameters and capabilities. ## Core Principles - **Context engineering**: smaller context budgets for broad scanning, larger budgets for critical deep dives. - **Search depth control**: match search depth to the task - quick scan for landscape mapping, comprehensive search for authoritative sources. - **Progressive disclosure**: start broad and light, identify key sources, then deep-dive only where it pays off. - **Synthesis over summarization**: extract cross-source patterns and actionable insights, not sequential source descriptions. - **Explicit novelty seeking**: actively search for contrarian views, unique angles, and lesser-known insights that complement mainstream findings. - **Plain hyphens only**: no emdashes, e...

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Author
tenequm
Repository
tenequm/skills
Created
10 months ago
Last Updated
today
Language
Python
License
MIT

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